This paper investigates a proactive eavesdropping scenario where multiple suspicious communication (SC) links are eavesdropped by a full-duplex monitor who can send jamming or constructive signals on each SC link. In order to avoid being discovered by the suspicious users, the monitor restricts the SC quality-of-service (QoS) degradation caused by itself. Under this SC QoS constraint and the average transmit power constraint, the problems of optimizing the mode and transmit power of the monitor to maximize the average successful eavesdropping probability and the average eavesdropping rate are investigated for the delay-sensitive suspicious service and delay-tolerant suspicious service, respectively. By proving that the time-sharing condition is satisfied, the optimal solutions are derived based on the Lagrange duality method. Simulation results validate the effectiveness of the proposed schemes. It is shown that the proposed schemes can provide satisfactory eavesdropping performance improvement even with zero SC QoS degradation requirement.
This paper investigates a proactive eavesdropping scenario where multiple suspicious communication (SC) links are eavesdropped by a full-duplex monitor who can send jamming or constructive signals on each SC link. In order to avoid being discovered by the suspicious users, the monitor restricts the SC quality-of-service (QoS) degradation caused by itself. Under this SC QoS constraint and the average transmit power constraint, the problems of optimizing the mode and transmit power of the monitor to maximize the average successful eavesdropping probability and the average eavesdropping rate are investigated for the delay-sensitive suspicious service and delay-tolerant suspicious service, respectively. By proving that the time-sharing condition is satisfied, the optimal solutions are derived based on the Lagrange duality method. Simulation results validate the effectiveness of the proposed schemes. It is shown that the proposed schemes can provide satisfactory eavesdropping performance improvement even with zero SC QoS degradation requirement.
In this letter, legitimate surveillance of a pair of suspicious users (SUs) who shares the same spectrum with a pair of unsuspicious users (UUs), in the presence of a full-duplex monitor, is investigated. The monitor can proactively jam the suspicious communication for better eavesdropping performance. The problem of jamming transmit power optimization for maximizing the successful eavesdropping probability under the constraint that the quality of service (QoS) of the UUs is not affected, is investigated. After important properties of the problem are obtained, a high-complexity optimal algorithm and a low-complexity suboptimal algorithm are derived. The superiority of the proposed algorithms compared to the benchmark algorithm is verified by simulation results.
Proactive eavesdropping is an effective approach to improve the performance of wireless information surveillance, where suspicious users are legitimately eavesdropped by authorized monitors. For the situation when no monitor is available, we propose to authorize unsuspicious users to surveil suspicious users provided that the quality-of-service (QoS) of unsuspicious users is guaranteed. This paper considers an interference network consisting of a suspicious-transmitter (STx)/suspicious-receiver (SRx) pair and an unsuspicious-transmitter (UTx)/unsuspicious-receiver (URx) pair. We assume that URx acts as a monitor to eavesdrop the suspicious communication, and UTx adopts improper Gaussian signaling (IGS) for flexibly managing the interference to SRx. The QoS of the unsuspicious communication is guaranteed by enforcing its outage performance to be higher than a desirable level. The problem of optimizing the transmit power and the IGS circularity coefficient of UTx to maximize the average eavesdropping rate is optimally solved by the Lagrange duality method. Theoretical results show that IGS is effective when the eavesdropping is successful and the unsuspicious communication is in non-outage status. Simulation results confirm that the proposed design works well even when no additional outage of the unsuspicious communication is allowed, and show that IGS can greatly outperform proper Gaussian signaling in most cases.
Short packet communications play key roles in the Internet-of-Things. Conventional Shannon’s coding theorem is not applicable for short packet communications, and the achievable rate in the finite blocklength regime is related to the blocklength and the decoding error probability. Contrary to conventional physical layer security, wireless information surveillance assumes that the communication users are suspicious users and the eavesdroppers are legitimate monitors, and proactive eavesdropping via jamming has been proposed to improve the eavesdropping performance. Existing works on proactive eavesdropping ignored the scenario when the suspicious users adopt the short packet communications. Thus, this paper tries to develop effective proactive eavesdropping schemes suitable for the short packet suspicious communications. Under the truncated channel inversion power allocation and the modified constant power allocation policies at the suspicious source, the problems of jamming power allocation for maximizing the monitoring success probability subject to the average transmit power constraint at the monitor are investigated. Based on the Dinkelbach-type algorithm, the Lagrange duality method and a novel tractable approximate expression for the decoding error probability, we derive suboptimal solutions to the problems. Simulation results demonstrate the effectiveness of the proposed solutions compared to various benchmark algorithms in existing literature.
Surveillance performance is studied in this paper for a wireless eavesdropping system, where a full-duplex legitimate monitor eavesdrops a suspicious link efficiently with the artificial noise (AN) assistance. Different from the existing work, the suspicious receiver is assumed to be capable of detecting the presence of AN. Once such receiver detects the AN, the suspicious user will stop transmission, which degrades the surveillance performance. Hence, to improve the surveillance performance, AN should be transmitted covertly with a low detection probability. Under these assumptions, an optimization problem is formulated to maximize the eavesdropping non-outage probability under a covert constraint. Based on the detection ability at the suspicious receiver, a novel scheme is proposed to solve the optimization problem using an iterative search. Moreover, we investigate the impact of both the suspicious and the jamming links uncertainties on the covert surveillance performance. Simulations are performed to verify the analyses. We show that the suspicious link uncertainty enhances the surveillance performance, while the jamming link uncertainty can degrade the surveillance performance.
To enhance the national security, there is a growing need for government agencies to legitimately monitor suspicious communication links for preventing intended crimes and terror attacks. In this paper, we propose a new wireless information surveillance paradigm by investigating a scenario where a legitimate monitor aims to intercept a suspicious wireless communication link over fading channels. The legitimate monitor can successfully eavesdrop (decode) the information of the suspicious link at each fading state only when its achievable data rate is no smaller than that at the suspicious receiver. In practice, such legitimate eavesdropping is particularly challenging, since the legitimate monitor may be far away from the suspicious transmitter and cannot eavesdrop efficiently. To overcome this issue, we propose a new approach, namely proactive eavesdropping via cognitive jamming, in which the legitimate monitor purposely jams the receiver so as to change the suspicious communication (e.g., to a smaller data rate) for overhearing more efficiently. In particular, we consider delay-sensitive and delay-tolerant applications for the suspicious data communications, under which the legitimate monitor maximizes the eavesdropping non-outage probability for event-based monitoring and the relative eavesdropping rate for content analysis, respectively, by optimizing its jamming power allocation over different fading states subject to an average power constraint. Numerical results show that the proposed proactive eavesdropping via cognitive jamming approach greatly outperforms the conventional passive eavesdropping without jamming and the proactive eavesdropping with constant-power jamming.
To enhance the national security, there is a growing need for authorized parties to legitimately monitor suspicious communication links for preventing intended crimes and terror attacks. In this paper, we propose a new wireless information surveillance paradigm by investigating a scenario, where a legitimate monitor aims to intercept a suspicious wireless link over fading channels. The legitimate monitor can successfully eavesdrop (decode) the information of the suspicious link at each fading state only when its achievable data rate is no smaller than that at the suspicious receiver. We propose a new approach, namely, proactive eavesdropping via cognitive jamming, in which the legitimate monitor purposely jams the receiver in a full-duplex mode so as to change the suspicious communication (e.g., to a smaller data rate) for overhearing more efficiently. By assuming perfect self-interference cancelation (SIC) and global channel state information (CSI) at the legitimate monitor, we characterize the fundamental information-theoretic limits of proactive eavesdropping. We consider both delay-sensitive and delay-tolerant applications for the suspicious communication, under which the legitimate monitor maximizes the eavesdropping non-outage probability (for event-based monitoring) and the relative eavesdropping rate (for content analysis), respectively, by optimizing the jamming power allocation over different fading states subject to an average power constraint. Numerical results show that the proposed proactive eavesdropping via cognitive jamming approach greatly outperforms other benchmark schemes. Furthermore, by extending to a more practical scenario with residual SI and local CSI, we design an efficient online cognitive jamming scheme inspired by the optimal cognitive jamming with perfect SIC and global CSI.